Data Scientist - Resilience Modeling

One Concern is a Menlo Park-based benevolent artificial intelligence company with a mission to increase the global community's resilience to natural hazards. Founded at Stanford University, One Concern enables cities, corporations, and citizens to embrace a disaster-free future through AI-enabled technology, policy, and finance. By combining data science and natural phenomena science we are pursuing a vision for planetary-scale resilience, where everyone lives in a safe, equitable, and sustainable world.One Concern is growing rapidly and we are looking for a passionate and motivated Data Scientist for Model Validation to join our team. In your role, you will be responsible for execution of validation activities for disaster models, model performance evaluations, and working with product teams to ensure that models and metrics meet customer objectives.

What you will do

• Build a global-scale resilience model to predict the societal and economic impact and recovery of the built environment against disasters
• Build and improve existing machine learning models
• Work with and support domain experts and data scientists in different hazard products
• Demonstrate up-to-date machine learning skills and apply this to the development, execution, and improvement of action plans
• Assess the potential usefulness and validity of new statistical approaches and data sources.
• Identify key problems in prediction models and propose innovative solutions
• Formulate your own problems as the problem might not always be defined for you
• Collaborate with an interdisciplinary team of software engineers and data scientists on cross-functional projects, interpreting data, and translating into actionable insights

Must-haves

• Ph.D. (preferred) or Master’s degree in Machine Learning, Computer Science, Statistics, Mathematics, Engineering, Science or related field 
• Strong background in machine learning, statistics, and quantitative analytics
• Experience in developing machine-learning models and/or statistical/probabilistic models
• Proficient in Python

Good to have

• Domain knowledge of natural disasters or risk modeling.
• Strong publication record